head to head · open source
Milvus vs Weaviate
Milvus has 46,563 GitHub stars, 4,325 forks, 1,405 open issues and last shipped yesterday. Weaviate has 16,934 stars, 1,433 forks, 738 open issues and last shipped yesterday. Milvus leads on adoption by 175% (46,563 vs 16,934 stars). Milvus is written in Go under Apache-2.0; Weaviate is written in Go under a custom or non-standard licence. Milvus has attracted 9% as many forks as stars, Weaviate 8%. Weaviate was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 2 topic tags (hnsw, image-search), so they are genuine substitutes rather than adjacent tools.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| Milvus | Weaviate | |
|---|---|---|
| GitHub stars | ★ 47K | ★ 17K |
| License | Apache-2.0 | Custom / other |
| Written in | Go | Go |
| Last push | 2026-11-02 | 2026-11-02 |
| Forks | ⑂ 4.3K | ⑂ 1.4K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Milvus if
- You weight community size — 47K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Go
- You value the larger contributor base for long-term maintenance
pick Weaviate if
- You want the Weaviate feature set and don't need the biggest community
- You prefer the Custom / other license terms
- Your stack matches Go
- You evaluated both and Weaviate fits your workflow better
About Milvus
What is Milvus? 🐦 Milvus is a high performance vector database built for scale. It powers AI applications by efficiently organizing and searching vast amounts of unstructured data, such as text, images, and multi modal information. 🧑💻 Written in Go and C++, Milvus implements hardware acceleration for CPU/GPU to achieve best in class vector search performance. Thanks to its fully distributed and K8s native architecture, Milvus can scale horizontally, handle tens of thousands of search queries on billions of vectors, and keep data fresh with real time streaming updates. Milvus also supports Standalone mode for…
read the full Milvus overview →
About Weaviate
Weaviate Weaviate is an open source, cloud native vector database that stores both objects and vectors, enabling semantic search at scale. It combines vector similarity search with keyword filtering, retrieval augmented generation (RAG), and reranking in a single query interface. Common use cases include RAG systems, semantic and image search, recommendation engines, chatbots, and content classification. Weaviate supports two approaches to store vectors: automatic vectorization at import using integrated models (OpenAI, Cohere, HuggingFace, and others) or direct import of pre computed vector embeddings…
read the full Weaviate overview →
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Frequently asked questions
Is Milvus or Weaviate more popular?
Milvus has 46,563 GitHub stars and Weaviate has 16,934. Milvus has the larger community by that measure.
Are Milvus and Weaviate free?
Both are open source. Milvus is licensed under Apache-2.0, and Weaviate has no licence declared in this registry. Both are free to self-host.
What is the difference between Milvus and Weaviate?
Milvus is written in Go and Weaviate in Go. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Milvus or Weaviate?
Choose Milvus if you want the larger community (46,563 stars) or its Apache-2.0 licence terms. Choose Weaviate if its feature set, stack or Custom / other licence fits better. Both are self-hostable.